| Benchmark | Model | Rank | Results |
|---|---|---|---|
| image-classification-on-cifar-10 | FGS (ConvNeXt-L, Laion-2B) | – | Percentage correct: 98.78 |
| image-classification-on-cifar-100 | FGS (Swin-L, ImageNet-21K) | – | Percentage correct: 91.48 |
| image-classification-on-flowers-102 | FGS (Swin-L, ImageNet-21K) | – | Accuracy: 99.54 |